Energy-Related Data Integration Using Semantic Data Models for Energy Efficient Retrofitting Projects

Álvaro Sicilia Gómez; Gonçal Costa Jutglar

doi:10.3390/proceedings1071099

Energy-Related Data Integration Using Semantic Data Models for Energy Efficient Retrofitting Projects

Álvaro Sicilia Gómez, Gonçal Costa Jutglar

Research output: Book chapter › Conference contribution › peer-review

Abstract

Energy efficient retrofitting projects of urban areas require to analyze data from multiple sources and domains—BIM, GIS, statistics, energy data, and climate. An interoperability solution is needed to overcome the semantic and structural heterogeneity of the data sources. Within OptEEmAL project, we have design and implemented a District Data Model which integrates multiple data sources and makes them interoperable with several simulation tools (Energy plus, Nest, CitySim) using Semantic Web technologies, namely, ontologies and SPARQL construct queries.

Original language	English
Title of host publication	Proceedings of the Sustainable Places 2017 (SP2017)
Place of Publication	Middlesbrough, UK
Publisher	MDPI
Chapter	1 (7)
DOIs	https://doi.org/10.3390/proceedings1071099
Publication status	Published - 5 Dec 2017

Keywords

Energy efficiency retrofitting
semantic web
Linked Data
Data integration
Ontologies
SPARQL

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.3390/proceedings1071099Licence: Unspecified

Cite this

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title = "Energy-Related Data Integration Using Semantic Data Models for Energy Efficient Retrofitting Projects",

abstract = "Energy efficient retrofitting projects of urban areas require to analyze data from multiple sources and domains—BIM, GIS, statistics, energy data, and climate. An interoperability solution is needed to overcome the semantic and structural heterogeneity of the data sources. Within OptEEmAL project, we have design and implemented a District Data Model which integrates multiple data sources and makes them interoperable with several simulation tools (Energy plus, Nest, CitySim) using Semantic Web technologies, namely, ontologies and SPARQL construct queries.",

keywords = "Energy efficiency retrofitting, semantic web, Linked Data, Data integration, Ontologies, SPARQL",

author = "{Sicilia G{\'o}mez}, {\'A}lvaro and {Costa Jutglar}, Gon{\c c}al",

year = "2017",

month = dec,

day = "5",

doi = "10.3390/proceedings1071099",

language = "English",

booktitle = "Proceedings of the Sustainable Places 2017 (SP2017)",

publisher = "MDPI",

address = "Switzerland",

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TY - GEN

T1 - Energy-Related Data Integration Using Semantic Data Models for Energy Efficient Retrofitting Projects

AU - Sicilia Gómez, Álvaro

AU - Costa Jutglar, Gonçal

PY - 2017/12/5

Y1 - 2017/12/5

N2 - Energy efficient retrofitting projects of urban areas require to analyze data from multiple sources and domains—BIM, GIS, statistics, energy data, and climate. An interoperability solution is needed to overcome the semantic and structural heterogeneity of the data sources. Within OptEEmAL project, we have design and implemented a District Data Model which integrates multiple data sources and makes them interoperable with several simulation tools (Energy plus, Nest, CitySim) using Semantic Web technologies, namely, ontologies and SPARQL construct queries.

AB - Energy efficient retrofitting projects of urban areas require to analyze data from multiple sources and domains—BIM, GIS, statistics, energy data, and climate. An interoperability solution is needed to overcome the semantic and structural heterogeneity of the data sources. Within OptEEmAL project, we have design and implemented a District Data Model which integrates multiple data sources and makes them interoperable with several simulation tools (Energy plus, Nest, CitySim) using Semantic Web technologies, namely, ontologies and SPARQL construct queries.

KW - Energy efficiency retrofitting

KW - semantic web

KW - Linked Data

KW - Data integration

KW - Ontologies

KW - SPARQL

U2 - 10.3390/proceedings1071099

DO - 10.3390/proceedings1071099

M3 - Conference contribution

BT - Proceedings of the Sustainable Places 2017 (SP2017)

PB - MDPI

CY - Middlesbrough, UK

ER -

Energy-Related Data Integration Using Semantic Data Models for Energy Efficient Retrofitting Projects

Abstract

Keywords

UN SDGs

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